Microfluidics with feedback control and machine learning (Conference Presentation)

Desmond Quinn; Tobias Thalheim; Frank Cichos

doi:10.1117/12.2633484

4 October 2022 Microfluidics with feedback control and machine learning (Conference Presentation)

Desmond Quinn, Tobias Thalheim, Frank Cichos

Proceedings Volume PC12204, Emerging Topics in Artificial Intelligence (ETAI) 2022; PC122040S (2022) https://doi.org/10.1117/12.2633484
Event: SPIE Nanoscience + Engineering, 2022, San Diego, California, United States

Abstract

Microfluidics is commonly ruled by pressure driven flows enabling the transport of material on large scales incorporating different kinds of functionality for sensing flow control or chemical synthesis. Yet, a local control of fluids and dissolved species is difficult due to the macroscopic nature of the exerted pressure gradients. Here we present our efforts to control liquids and dissolved species at the microscale using thermo-fluidic approaches. We employ optically controlled thermo-osmotic, thermophoretic, and thermoviscous flows to induce fluid flow to sense, localise, or separate different species in solution. We introduce different spectroscopic and microscopic signals to report on the local properties and composition of the solution with the help of machine learning approaches to track and classify species in real time to provide a feedback to steer the system into desired directions.

Conference Presentation

Citation Download Citation

Desmond Quinn, Tobias Thalheim, and Frank Cichos "Microfluidics with feedback control and machine learning (Conference Presentation)", Proc. SPIE PC12204, Emerging Topics in Artificial Intelligence (ETAI) 2022, PC122040S (4 October 2022); https://doi.org/10.1117/12.2633484

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